value: "Identity:output:0"
    }
    # The attribute "experimental_ints_on_device" and the return type INT32
    # ensure that kDeviceRetOp is used instead of kRetOp
    # CHECK-LABEL: func private @foo
    # CHECK:    tf.experimental_ints_on_device = true
    # CHECK:    return %{{.*}} tensor<{{.*}}i32>
    attr {
      key: "experimental_ints_on_device"
      value {
        b: true
      }
    }
  }
}

      %gen0 = "tf.GeneratorDataset"(%str, %arg0, %arg1, %arg2, %arg3) {
        finalize_func = @__finalize_func_790,
        init_func = @__init_func_530, next_func = @__next_func_680,
        next_func.experimental_ints_on_device = true,
        operandSegmentSizes = array<i32: 2, 2, 1>,
        output_shapes = [#tf_type.shape<?>],
        output_types = [f32],
        metadata = ""
      } :

      %gen0 = "tf.GeneratorDataset"(%str, %arg0, %arg1, %arg2, %arg3) {
        finalize_func = @__finalize_func_790,
        init_func = @__init_func_530, next_func = @__next_func_680,
        next_func.experimental_ints_on_device = true,
        operandSegmentSizes = array<i32: 2, 2, 1>,
        output_shapes = [#tf_type.shape<?>],
        output_types = [f32],
        metadata = ""
      } :

        %0 = "tf.GeneratorDataset"(%arg0, %arg0, %arg0) {device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0", finalize_func = @__func_a, init_func = @__func_b, next_func = @__func_c, next_func.experimental_ints_on_device = true, operandSegmentSizes = array<i32: 1, 1, 1>, output_shapes = [#tf_type.shape<>], output_types = [!tf_type.string], metadata = ""} : (tensor<!tf_type.string>, tensor<!tf_type.string>, tensor<!tf_type.string>) -> tensor<!tf_type.variant>...